Abstract
Various approach including artificial neural networks have been used to classify a large image database efficiently and shown to be highly successful in this application area. This paper presents a new, scaling and rotation invariant encoding scheme for shapes. Support vector machines (SVMs) are used for the classifications of shapes encoded by the new method. This paper examines the performance of the proposed method by comparing it with that of multilayer perception, one of the artificial neural network (ANNs) techniques, based on real real-world image data. The experiment shows that the results of one-class SVMs outperform those of ANNs.
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Acknowledgments
This research was supported by the Natural Science Foundation of Luoyang Institute of Science and Technology (Grant No. 2008QZ28).
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© 2013 Springer-Verlag London
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Wang, G., Cui, W., Sun, C. (2013). An Approach for Image Retrieval Based on Support Vector Machines. In: Du, W. (eds) Informatics and Management Science V. Lecture Notes in Electrical Engineering, vol 208. Springer, London. https://doi.org/10.1007/978-1-4471-4796-1_92
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DOI: https://doi.org/10.1007/978-1-4471-4796-1_92
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